void FiltMaxImg(const Img& in, const int k_width, const int k_height, const int channel, Img& out) {
const int width = in.width();
const int height = in.height();
const int num_channel = in.channel();
assert(num_channel > channel);
out.Reshape(width, height, 1);
const double* in_data = in.data();
double* out_data = out.mutable_data();
for(int h = 0; h < height; h++) {
for (int w = 0; w < width; w++) {
int w_start = w - ((k_width) / 2);
int h_start = h - ((k_height) / 2);
int kw_start = 0;
int kh_start = 0;
int kw_end = k_width;
int kh_end = k_height;
double max_value = -MAX_DOUBLE;
for (int i = kh_start; i < kh_end; i++ ) {
for (int j = kw_start; j < kw_end; j++) {
int w_temp = w_start + j;
int h_temp = h_start + i;
if (w_temp >=0 && w_temp < width && h_temp >= 0 && h_temp < height) {
max_value = std::max(max_value, in_data[h_temp * width + w_temp]);
}
}
}
out_data[h * width + w] = max_value;
}
}
}
void FiltMedImg(const Img& in, const int k_width, const int k_height, const int channel, Img& out) {
const int width = in.width();
const int height = in.height();
const int num_channel = in.channel();
assert(num_channel > channel);
out.Reshape(width, height, 1);
const double* in_data = in.data();
double* out_data = out.mutable_data();
for(int h = 0; h < height; h++) {
for (int w = 0; w < width; w++) {
int w_start = w - ((k_width) / 2);
int h_start = h - ((k_height) / 2);
int kw_start = 0;
int kh_start = 0;
int kw_end = k_width;
int kh_end = k_height;
std::vector<double> temp_list;
for (int i = kh_start; i < kh_end; i++ ) {
for (int j = kw_start; j < kw_end; j++) {
int w_temp = w_start + j;
int h_temp = h_start + i;
if (w_temp >=0 && w_temp < width && h_temp >= 0 && h_temp < height) {
temp_list.push_back(in_data[h_temp * width + w_temp]);
}
}
}
std::sort(temp_list.begin(), temp_list.end());
out_data[h * width + w] = temp_list[temp_list.size()/2];
}
}
}
int main() {
float scale = 400.f;
float offset_x = 5.9f;
float offset_y = 5.1f;
float offset_z = 0.05f;
float lacunarity = 1.99f;
float persistance = 0.5f;
Img img;
while (!img.is_closed()) {
Measure measure;
measure.start();
const SimplexNoise simplex(0.1f/scale, 0.5f, lacunarity, persistance); // Amplitude of 0.5 for the 1st octave : sum ~1.0f
const int octaves = static_cast<int>(5 + std::log(scale)); // Estimate number of octaves needed for the current scale
std::ostringstream title;
title << "2D Simplex Perlin noise (" << octaves << " octaves)";
img.set_title(title.str().c_str());
for (int row = 0; row < img.height(); ++row) {
const float y = static_cast<float>(row - img.height()/2 + offset_y*scale);
for (int col = 0; col < img.width(); ++col) {
const float x = static_cast<float>(col - img.width()/2 + offset_x*scale);
// TODO(SRombauts): Add 'erosion' with simple smoothing like exponential, and other 'modifiers' like in libnoise
// Generate "biomes", ie smooth geographic variation in frequency & amplitude,
// and add smaller details, summing the noise values for the coordinate
const float noise = simplex.fractal(octaves, x, y) + offset_z;
const color3f color = ramp(noise); // convert to color
img.draw_point(col, row, (float*)&color);
}
}
img.display();
const double diff_ms = measure.get();
std::cout << std::fixed << diff_ms << "ms\n";
img.user(scale, offset_x, offset_y, offset_z, lacunarity, persistance);
}
return 0;
}
void FiltImg(const Img& in, const Img& filter, const int channel, Img& out) {
const int width = in.width();
const int height = in.height();
const int num_channel = in.channel();
assert(num_channel > channel);
out.Reshape(width, height, 1);
const double* in_data = in.data() + channel * out.dim();
const double* filter_data = filter.data();
double* out_data = out.mutable_data();
const int k_width = filter.width();
const int k_height = filter.height();
for(int h = 0; h < height; h++) {
for (int w = 0; w < width; w++) {
int w_start = w - ((k_width) / 2);
int h_start = h - ((k_height) / 2);
int kw_start = 0;
int kh_start = 0;
int kw_end = k_width;
int kh_end = k_height;
double sum = 0;
for (int i = kh_start; i < kh_end; i++ ) {
for (int j = kw_start; j < kw_end; j++) {
int w_temp = w_start + j;
int h_temp = h_start + i;
if (w_temp >=0 && w_temp < width && h_temp >= 0 && h_temp < height) {
sum += in_data[h_temp * width + w_temp] * filter_data[i * k_width + j];
//printf("%f x %f, ", in_data[h_temp * width + w_temp], filter_data[i * k_width + j]);
//printf("%d %d, \n", h_temp, w_temp);
}
}
}
out_data[h * width + w] = sum;
}
}
}
